Bladder cancer (BCa) is the second most common genitourinary and fourth most common
cancer overall in the United States, with an estimated 81,400 newly diagnosed cases …

Objectives To comprehensively assess the diagnostic performance of Vesical Imaging-
Reporting and Data System (VI-RADS) score for detecting the muscle invasion of bladder …

Context Radiomics is a field of science that aims to develop improved methods of medical
image analysis by extracting a large number of quantitative features. New data have …

We aimed to develop a noninvasive radiomics approach to reveal the m6A methylation
status and predict survival outcomes and therapeutic responses in patients. A total of 25 …

Purpose To evaluate the diagnostic performance of image-based artificial intelligence (AI)
studies in predicting muscle-invasive bladder cancer (MIBC).(2) To assess the reporting …

Objective To build a CT-based radiomics model to predict the pathological grade of bladder
cancer (BCa) preliminarily. Methods Patients with surgically resected and pathologically …

Objectives This study investigated the feasibility of a computed tomography (CT)-based
radiomics prediction model to evaluate muscle invasive status in bladder cancer. Methods …

Background Clinical treatment decision making of bladder cancer (BCa) relies on the
absence or presence of muscle invasion and tumor staging. Deep learning (DL) is a novel …

Simple Summary This Part II is an overview of the main applications of Radiomics in
oncologic imaging with a focus on diagnosis, prognosis prediction and assessment of …

This study aimed to develop a versatile automatic segmentation model of bladder cancer
(BC) on MRI using a convolutional neural network and investigate the robustness of …